In our country's envisioned Society 5.0, Cyber-Physical Systems (CPS), which highly integrate cyberspace (virtual space) and physical space (real space), play a crucial role as foundational societal technologies. With the advancement of technologies such as AI, digital twins, IoT, autonomous mobile robots, and cloud/edge computing, CPS are rapidly being deployed in a wide range of societal fields, including smart mobility, healthcare, logistics, energy management, and disaster response.

In this laboratory, Estimation, Prediction, Control Research is conducted on topics such as networked control systems, robotics, machine learning, reinforcement learning, data-driven control, and AI-applied control. Specifically, research focuses on control system design considering communication constraints and uncertainties, state estimation and anomaly detection based on data, intelligent control of robots and drones, and learning-based control considering real-world environments. Furthermore, emphasis is placed on both simulation and actual experiments, aiming to realize intelligent systems that bridge theory and the real world.